AlphaGo Zero Explained In One Diagram
Download the AlphaGo Zero cheat sheet
Get the full cheat sheet here
Update! (2nd December 2019)
I’ve just released a series on MuZero — AlphaZero’s younger and cooler brother. Check it out 👇
How to Build Your Own MuZero Using Python (Part 1/3)
How to Build Your Own MuZero Using Python (Part 2/3)
Update! (26th January 2018)
I’ve just released a post on how you can build AlphaZero using Python and Keras. Check it out 👇
Recently Google DeepMind announced AlphaGo Zero — an extraordinary achievement that has shown how it is possible to train an agent to a superhuman level in the highly complex and challenging domain of Go, ‘tabula rasa’ — that is, from a blank slate, with no human expert play used as training data.
It thrashed the previous reincarnation 100–0, using only 4TPUs instead of 48TPUs and a single neural network instead of two.
The paper that the cheat sheet is based on was published in Nature and is available here. I highly recommend you read it, as it explains in detail how deep learning and Monte Carlo Tree Search are combined to produce a powerful reinforcement learning algorithm.
Hopefully you find the AlphaGo Zero cheat sheet useful — let me know if you find any typos or have questions about anything in the document.
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